1. Field of the Invention
The present invention generally relates to a pattern evaluation system, evaluation method and program for evaluating a pattern by measuring dimension and shape of the pattern.
2. Description of the Prior Art
As an example of a conventional pattern evaluation method, a method for evaluating a fine pattern of a semiconductor will be described below.
Evaluation of a pattern is important in a semiconductor fabricating process. This is particularly conspicuous with respect to a fine pattern formed in a lithography process and/or an etching process. Conventionally, there is generally adopted a method for measuring and evaluating the dimension of a pattern (e.g., a line width in the case of a line pattern, a hole diameter in the case of a hole pattern) by means of a CDSEM (Critical Dimension Scanning Electron Microscope) using electron beams. In a CDSEM, secondary electrons produced from a sample irradiated with primary electron beams are detected by a detector, and a SEM image of a pattern obtained as signal strength of the detected secondary electrons is processed to carry out a pattern evaluation, such as a dimension measurement. As a conventional pattern evaluation method using a CDSEM, a method for obtaining a line width of a line pattern will be described below.
First, a SEM image is acquired by scanning a sample with electron beams in a scanning line direction which is determined so as to be perpendicular to the longitudinal directions of a line pattern formed on the sample. Then, the SEM image is cut out in accordance with a region of interest (ROI) described on a measuring recipe or an ROI assigned by an operator, and is stored in, e.g., an image memory of a computer capable of processing images. Subsequently, assuming that the scanning line direction of the SEM system is X direction, an intensity distribution curve (a line profile) is prepared for every line pixel of the cut image in X direction. From this profile, coordinates of edge points of the pattern are extracted by, e.g., the threshold method. In this case, right and left two edge points (X-coordinates) are extracted. Then, the distance between these edge points (the difference between the X-coordinates) is determined as the width of this line pixel of the line pattern, and the width of each line pixel is calculated. The mean value of the calculated values in the longitudinal directions of the ROI is finally outputted as the width of the line pattern. There are some cases where the calculated value fluctuates due to noises of the image. Therefore, in order to remove this fluctuation, for example, the mean value of the widths of three line pixels including upper and lower line pixels may be obtained to determine the mean value as the width of the line pixel, or the mean value of values of distance between the edge points in the longitudinal directions of the ROI may be finally outputted as the width of the line pattern. Furthermore, if the variation in width in the longitudinal directions of an ROI is small like a line pattern, the calculation time is generally shortened by thinning line pixels to calculate the width.
Then, the following two steps are required for carrying out an image processing when the dimension of a pattern is to be measured. That is, there are required a step of detecting the edge of the pattern using an edge detecting algorithm, and a step of calculating the dimension of the pattern by a CD measuring algorithm suitable for the object of measurement. There are some method for the CD measuring algorithm of these algorithms such as a method in which the mean value of distance between edge points is used like the above example and a simple method in which, e.g., the maximum or minimum distance between edge points is calculated as the maximum or minimum line width in the case that a line pattern does not have a constant width as well as a method requiring a complicated calculating procedure as disclosed in Japanese Patent Laid-Open No. 2000-171230. In either of these methods, the threshold method, the straight line approximation, the maximum gradient method or the like is used as the pattern edge detecting algorithm prior to the method. These methods in the prior art are described in Japanese Patent Laid-Open No. 9-1 84714.
However, in the above described conventional method for detecting the edge points of the pattern, there are some cases where no edge can be detected or an incorrect edge is detected by mistake, in accordance with the shape and arrangement of the pattern. In the above described conventional method, there are also some cases where the measured value of the dimension of the pattern varies in accordance with the size of the ROI for cutting out the pattern. In addition, in the above described conventional method, it is necessary to assign the ROI. Therefore, if the shape of the pattern is complicated, it is required to carry out a complicated procedure of assigning the ROI, so that the burden on the operator increases and the reliability of automatic measurement decreases. In addition, in the above described conventional method, there are some cases where the measured value of the dimension of the pattern varies in accordance with the variation in contrast/brightness of the pattern or the variation in tapered angle of the side wall of the pattern. Moreover, in the above described conventional method, there is a problem in that the measured value or the like of the dimension of the pattern depends on the magnification in measurement.